This repository contains all the programming exercises in Python for the Coursera course called "Machine Learning" by Adjunct Professor Andrew Ng at Stanford University.
- Written in Python3 using Jupyter Notebook.
- Explains the derivations in detail.
- Discusses few topics (not covered in course)in detail.
- Mainly uses pandas and numpy library.
- Zero use of sklearn and like libraries.
Course : Machine Learning (Stanford University)
- Exercise 1 : Linear Regression
- Exercise 2 : Logistic Regression
- Exercise 3 : Multi-class Classification and Neural Networks
- Exercise 4 : Neural Networks Learning
- Exercise 5 : Regularized Linear Regression and Bias v.s. Variance
- Exercise 6 : Support Vector Machines
- Exercise 7 : K-means Clustering and Principal Component Analysis
- Exercise 8 : Anomaly Detection and Recommender Systems
